Method and system for verifying quality of server

ABSTRACT

A method and a system for verifying quality of server thereof are provided. The method and the system are used for verifying a plurality of servers constructed in a server cluster. The method includes: installing a cloud computing platform in the servers, creating an input file folder on a cloud computing platform file system included in the cloud computing platform and storing calculation data into the input file folder. The method further includes: creating a plurality of mapreduce tasks corresponding to a calculation job by the servers and distributively executing the mapreduce tasks by using a mapreduce frame included in the cloud computing platform to obtain a plurality of calculation results, and storing and analyzing the calculation results to verify a quality of each of the servers. Accordingly, the method is capable of conformably verifying quality of servers in the server cluster.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan applicationserial no. 102146708, filed on Dec. 17, 2013. The entirety of theabove-mentioned patent application is hereby incorporated by referenceherein and made a part of this specification.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention relates to a method and a system for verifying quality ofserver, and more particularly to a method and a system for verifyingquality of servers for a plurality of servers constructed in a servercluster.

2. Description of Related Art

In recent years, with the rapid spread of the Internet and improvementsin software and hardware technology, demands for information servicesare increasingly high in many companies. Accordingly, an integratedcomputer with high-speed calculation and massive storage capabilityformed by combining numerous servers through Internet is widely used bycompanies nowadays. For server manufacturers, servers trends to massproduction. Namely, as the servers are developed more complex in termsof both function and structure, it is more difficult to verify qualityof the servers.

Traditionally, in the era when the servers are still operatedindependently from one another, when it comes to verify quality of theservers, since each of the servers may include a functional verificationwhich is individually designed, there will not be any problem even ifthe servers are operated in the same room. However, today's servers areof server types mainly based on Blade Server or Rack Mount server, thusvarious resources are usually connected and shared between the servers.In other words, services provided by the servers are no longer completedby single server alone. Currently, in the field for verifying quality ofserver, methods for verifying quality of server still stay in verifyinghardware, firmware and software for one single server. Accordingly, howto maintain stability of each server under operations by numerousservers while providing higher performance in verifying quality of thenumerous servers in a server cluster has become a major issue to besolved in the field for verifying quality of server.

SUMMARY OF THE INVENTION

The invention is directed to a method and a system for verifying qualityof server, capable of verifying numerous servers in a server clusterthrough a cloud computing platform at the same time, so as to ensurequality of the servers.

The invention provides a method for verifying quality of server, usedfor verifying a plurality of servers constructed in a server cluster.The method includes: installing a cloud computing platform in theservers in the server cluster, and the cloud computing platform includesa cloud computing platform file system and a mapreduce frame; creatingan input file folder on the cloud computing platform file system andstoring a calculation data into the input file folder; creating aplurality of mapreduce tasks corresponding to a calculation job by theservers, accessing the calculation data in the input file folder, anddistributively executing the mapreduce tasks by using the mapreduceframe to obtain a plurality of calculation results; and storing andanalyzing the calculation results to verify a quality of each of theservers.

In an exemplary embodiment of the invention, the servers further includea main server and a plurality of node servers, and the step of creatingthe mapreduce tasks corresponding to the calculation job by the servers,accessing the calculation data in the input file folder, anddistributively executing the mapreduce tasks by using the mapreduceframe to obtain the calculation results includes: dividing thecalculation job into the mapreduce tasks by the main server; assigningthe mapreduce tasks to the main server and the node servers; andexecuting the mapreduce tasks respectively by the main server and thenode servers.

In an exemplary embodiment of the invention, the method for verifyingquality of server further includes: after installing the cloud computingplatform in the servers in the server cluster, writing a name of themain server and names of the node servers into a corresponding profile;restarting the cloud computing platform installed in the servers;determining whether the node servers are connected to the main server;and if the node servers are not connected to the main server, restartingthe cloud computing platform.

In an exemplary embodiment of the invention, the cloud computingplatform further includes a distributed data storage system, and thestep of storing the calculation results includes: transmitting thecalculation results to the distributed data storage system and storingthe calculation results into a database.

In an exemplary embodiment of the invention, the step of analyzing thecalculation results to verify the quality of each of the serversincludes: determining an operation condition of each of the serversduring execution of the calculation job according to a registrygenerated after the calculation job is executed by the server cluster.

In an exemplary embodiment of the invention, the step of executing themapreduce tasks respectively by the main server and the node serversincludes: reading the calculation data from the input file folder by themain server and the node servers and executing a plurality of mappers inthe mapreduce tasks for the calculation data; and executing a pluralityof reducers in the mapreduce tasks according to the calculation resultsby the main server and the node servers.

In an exemplary embodiment of the invention, the calculation job is asquare root calculation.

The invention provides a system for verifying quality of server, usedfor a plurality of servers constructed in a server cluster. The systemincludes a calculation platform installing module, a file and datacreating module, a server calculation module, a calculation resultprocessing module, and a calculation result analysis module. Thecalculation platform installing module is configured to install a cloudcomputing platform in the servers, and the cloud computing platformincludes a cloud computing platform file system and a mapreduce frame.The file and data creating module is configured to create an input filefolder on the cloud computing platform file system and storing acalculation data into the input file folder. The server calculationmodule is configured to control each of the servers to create aplurality of mapreduce tasks corresponding to a calculation job, accessthe calculation data in the input file folder, and distributivelyexecute the mapreduce tasks by using the mapreduce frame to obtain aplurality of calculation results. The calculation result processingmodule is configured to process and storing the calculation results. Thecalculation result analysis module is configured to analyze thecalculation results to verify a quality of each of the servers.

In an exemplary embodiment of the invention, the servers further includea main server and a plurality of node servers.

In an exemplary embodiment of the inventions, the server calculationmodule is further configured to control the main server to assign themapreduce tasks to the main server and the node servers, and the servercalculation module is further configured to control the main server andthe node servers to execute the mapreduce tasks respectively.

In an exemplary embodiment of the invention, the system further includesa server setting module. The server setting module is configured to,after installing the cloud computing platform in the servers in theserver cluster, write names of the main server and the node servers intoa corresponding profile. The server setting module is further configuredto restart the cloud computing platform installed in the servers, anddetermining whether the node servers are connected to the main server.If the node servers are not connected to the main server, the serversetting module restarts the cloud computing platform.

In an exemplary embodiment of the invention, the cloud computingplatform further includes a distributed data storage system.

In an exemplary embodiment of the invention, the calculation resultprocessing module is further configured to transmit the calculationresults to the distributed data storage system and store the calculationresults into a database.

In an exemplary embodiment of the invention, the calculation resultanalysis module is further configured to determine an operationcondition of each of the servers during execution of the calculation jobaccording to a registry generated after the calculation job is executedby the server cluster.

In an exemplary embodiment of the invention, the server calculationmodule is further configured to control the main server and the nodeservers to read the calculation data from the input file folder andexecute a plurality of mappers in the mapreduce tasks for thecalculation data, and control the main server and the node servers toexecute a plurality of reducers in the mapreduce tasks according to thecalculation results.

In an exemplary embodiment of the invention, the calculation job is asquare root calculation.

Based on above, in the method and the system for verifying quality ofserver according to the invention, numerous servers are seriallyconnected through the cloud computing platform for conformably verifyingquality of numerous servers in the server cluster, which may effectivelyimprove performance for verifying quality of server.

To make the above features and advantages of the disclosure morecomprehensible, several embodiments accompanied with drawings aredescribed in detail as follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a system architecture forverifying quality of server according to an exemplary embodiment of theinvention.

FIG. 2 is a block diagram illustrating a cloud computing platformaccording to an exemplary embodiment of the invention.

FIG. 3 is a block diagram illustrating a server cluster installed withthe cloud computing platform according to an exemplary embodiment of theinvention.

FIG. 4 is a flowchart illustrating a setting method of a profile for thecloud computing platform and the servers according to an exemplaryembodiment of the invention.

FIG. 5 is a flowchart illustrating an assigning method of a calculationjob for verifying quality of server according to an exemplary embodimentof the invention.

FIG. 6 is a flowchart illustrating a method for verifying quality ofserver according to another exemplary embodiment of the invention.

DESCRIPTION OF THE EMBODIMENTS

In order to improve performance for verifying quality of the servercluster, numerous servers are serially connected through a cloudcomputing platform for verifying quality of a plurality of server in theserver cluster at the same time. Accordingly, performance for verifyingquality of the servers may be improved, and quality of each server maybe ensured by conformably verifying the same.

FIG. 1 is a block diagram illustrating a system architecture forverifying quality of server according to an exemplary embodiment of theinvention. It should be understood that, the example of FIG. 1 is merelyexemplary, and the invention is not limited thereto.

Referring to FIG. 1, a system architecture 100 for verifying quality ofserver includes a server cluster 110 and a system 120 for verifyingquality of server. The server cluster 110 includes a main server 112, afirst node server 114-1, a second node server 114-2, a third node server114-3 and a fourth node server 114-4. It should be noted that, it isillustrated with one main server and four node servers for example, butthe invention is not limited thereto. For instance, the systemarchitecture 100 for verifying quality of server may include a pluralityof server clusters, and each of the server clusters may include moreservers.

The main server 112, the first node server 114-1, the second node server114-2, the third node server 114-3 and the fourth node server 114-4 areconnected to one another through a network 140. Herein, the network 140may be a wired network or a wireless network.

The system 120 for verifying quality of server is connected to the mainserver 112, the first node server 114-1, the second node server 114-2,the third node server 114-3 and the fourth node server 114-4 through thenetwork 140, and used for verifying the first node server 114-1, thesecond node server 114-2, the third node server 114-3 and the fourthnode server 114-4 constructed in the server cluster 110.

The system 120 for verifying quality of server includes a microprocessor102, a buffer memory 104, a communication module 106, a calculationplatform installing module 122, a file and data creating module 124, aserver calculation module 126, a calculation result processing module128, a calculation result analysis module 130 and a server settingmodule 132.

The microprocessor 102 is configured to control overall operations ofthe system 120 for verifying quality of server. For instance, themicroprocessor 102 may be a central processing unit (CPU). Particularly,the microprocessor 102 may issue commands to the system 120 forverifying quality of server thereby verifying quality of servers in theserver cluster 110.

The buffer memory 104 is coupled to the microprocessor 102, andconfigured to temporarily store the commands executed by themicroprocessor 102, or data. For instance, in the present exemplaryembodiment, the buffer memory 104 may be a Dynamic Random Access Memory(DRAM), or a Static Random Access Memory (SRAM) and the like.Nevertheless, it should be understood that the invention is not limitedthereto, and the buffer memory 104 may also be other appropriatememories.

The communication module 106 is coupled to the microprocessor 102, andconfigured to communicate with the servers in the server cluster 110.For instance, the communication module 106 may be a wired or wirelesscommunication module.

FIG. 2 is a block diagram illustrating a cloud computing platformaccording to an exemplary embodiment of the invention.

Referring to FIG. 2, a cloud computing platform 200 based on Hadoop iscapable of providing an environment for distributed calculations of massdata. The cloud computing platform 200 includes a cloud computingplatform file system (Hadoop Distributed File System; HDFS) 202, amapreduce frame (MapReduce) 204, a distributed data storage system(Hive) 206.

More specifically, the cloud computing platform file system 202 iscapable of providing numerous storage spaces, and used for storing themass data in the cloud computing platform 200 and the temporary filesgenerated during calculations.

The mapreduce frame 204 is constructed on the cloud computing platformfile system 202, and configured to execute the distributed calculationsfor the mass data stored in the cloud computing platform file system 202in the server cluster. The distributed calculations may be applicationsincluding inquiring, indexing, sorting, data-mining for large data set,and website access analysis for large websites.

The distributed data storage system 206 is configured to manage datastored in the cloud computing platform file system 202. The distributeddata storage system 206 may inquire for the data stored in the cloudcomputing platform file system 202 by executing a query language basedon SQL.

In the present exemplary embodiment, the calculation platform installingmodule 122 is configured to install the cloud computing platform 200depicted in FIG. 2 in the main server 112, the first node server 114-1,the second node server 114-2, the third node server 114-3 and the fourthnode server 114-4 in the server cluster.

FIG. 3 is a block diagram illustrating a server cluster installed withthe cloud computing platform according to an exemplary embodiment of theinvention.

Referring to FIG. 3, after the cloud computing platform 200 is installedin each server in the server cluster 110 by the calculation platforminstalling module 122, the main server 112 and each of the node servers(114-1 to 114-4) may form an architecture as depicted in FIG. 3. Morespecifically, the main server 112 may include a name node (NameNode) 202a and a secondary name node (Secondary NameNode) 202 b provided by thecloud computing platform file system 202 as well as a job trackingmodule (JobTracker) 204 a provided by the mapreduce frame 204. Further,each of the node servers (114-1 to 144-4) may include a data node(DataNode) 202 c provided by the cloud computing platform file system202 as well as a task tracking module (TaskTracker) 204 b provided bythe mapreduce frame 204.

Referring back to FIG. 1, the file and data creating module 124 is usedfor creating an input file folder on the cloud computing platform filesystem 202 and storing a calculation data into the input file folder.

The server calculation module 126 is configured to control each of thenode servers (114-1 to 114-4) to create a plurality of mapreduce taskscorresponding to a calculation job, access the calculation data in theinput file folder, and distributively execute the mapreduce tasks byusing the mapreduce frame 204 to obtain a plurality of calculationresults.

The calculation result processing module 128 is configured to processand store the calculation results.

The calculation result analysis module 130 is configured to analyze thecalculation results thereby verifying a quality of each of the nodeservers (114-1 to 114-4).

FIG. 4 is a flowchart illustrating a setting method of a profile for thecloud computing platform and the servers according to an exemplaryembodiment of the invention.

Referring to FIG. 4, in step S401, after installing the cloud computingplatform 200 in all the servers in the server cluster 110, the serversetting module 132 may write names of the main server 112 and the nodeservers (114-1 to 114-4) into a corresponding profile. For instance, theserver setting module 132 may write IP addresses and the names of themain server 112 and each of the node servers (114-1 to 114-4) into afile “hosts” under a path “% WinDir %\system32\drivers\etc” in the mainserver 112, and write the name of the main server 112 and the name ofeach of the node servers (114-1 to 114-4) into files “master” and“slaves”, respectively, under a path “C: \Hadoop \hadoop-1.1.0-SNAP SHOT\conf\”.

In the present exemplary embodiment, the profile of the cloud computingplatform further includes “core-site.xml”, “mapred-site.xml” and“hdfs-site.xml” which are also under the path“C:\Hadoop\hadoop-1.1.0-SNAPSHOT\conf\”. Therefore, in step S401, theserver setting module 132 may further set names of all “localhost” inthe profiles in the main server 112 and each of the node servers (114-1to 114-4) to the name of the main server 112.

Subsequently, in step S403, the server setting module 132 may restartthe cloud computing platform 200 installed in each of the servers.

Thereafter, in step S405, the server setting module 132 may determinewhether each of the node servers (114-1 to 114-4) is connected to themain server 112. If the server setting module 132 determines that eachof the node servers (114-1 to 114-4) is not connected to the main server112, go back to step S403 in which the server setting module 132restarts the cloud computing platform 200 in each of the severs.

FIG. 5 is a flowchart illustrating an assigning method of a calculationjob for verifying quality of server according to an exemplary embodimentof the invention.

Referring to FIG. 5, in step S501, the server calculation module 126 maycontrol the main server 112 to divide the calculation job into themapreduce tasks.

In step S503, the server calculation module 126 is further used forcontrolling the job tracking module 204 a in the main server to assign aplurality of mapreduce tasks to the task tracking module 204 b in eachof the node servers (114-1 to 114-4).

Subsequently, in step S505, the server setting module 126 may controlthe task tracking module 204 b in each of the node servers (114-1 to114-4) to execute the mapreduce tasks being assigned, respectively.

It should be noted that, in the present exemplary embodiment, themapreduce task as described in step S505 is composed of a mapper and areducer. Particularly, the server setting module 126 may control each ofthe node servers (114-1 to 114-4) to read a calculation data from aninput file folder and execute a plurality of mappers in the mapreducetasks, and may control each of the node servers (1141 to 114-4) toexecute a plurality of reducers in the mapreduce tasks according tocalculation results.

In the present exemplary embodiment, the calculation result processingmodule 128 is further used for transmitting the calculation results tothe distributed data storage system 206 and storing the calculationresults into a database. More specifically, the distributed data storagesystem 206 may further include a database (Hbase, not illustrated), andsaid database is a distributed database on the distributed data storagesystem 206 for storing distributed data and the calculation results.

In another exemplary embodiment of the invention, the calculation resultanalysis module 130 is further used for determining an operationcondition of each of the node servers (114-1 to 114-4) during executionof the calculation job according to a registry generated after thecalculation job is executed by the server cluster 110.

FIG. 6 is a flowchart illustrating a method for verifying quality ofserver according to another exemplary embodiment of the invention.

Referring to FIG. 6, firstly, in step S601, the calculation platforminstalling module 122 may install the cloud computing platform 200 oneach of the servers in the server cluster 110.

Subsequently, in step S603, the file and data creating module 124 maycreate an input file folder on the cloud computing platform file system202 and store a calculation data into the input file folder. Forinstance, the file and data creating module 124 may use a cloudcomputing platform shell command (Hadoop shell) such as “hadoop fs-mkdirInput/sqrt” to create the input file folder on the cloud computingplatform file system 202, as well as “hadoop fs-put ‘filelist’Input/sqrt” to store the calculation data into the input file folder. Atthe time, the input file folder is distributed to the cloud computingplatform file system 202 in each of the servers.

In step S605, the server calculation module 126 may control each of thenode servers (114-1 to 114-4) to create a plurality of mapreduce taskscorresponding to a calculation job, access the calculation data in theinput file folder, and distributively execute the mapreduce tasks byusing the mapreduce frame 204 to obtain a plurality of calculationresults.

For example, in an exemplary embodiment of the invention, the servercalculation module 126 may use the mapreduce frame 204 to execute asquare root calculation for the calculation data. More specifically, theserver calculation module 126 may control the data node 202 c in each ofthe node servers (114-1 to 114-4) to access the calculation data in theinput file folder. Particularly, the mapreduce task is composed of amapper and a reducer. When the mapper is executed, the servercalculation module 126 may control the task tracking module 204 b ineach of the node servers (114-1 to 114-4) to execute the square rootcalculation for the calculation data in the input file folder, and thecalculation are then counted and arranged when the reducer is executed.It should be noted that, assignment of the calculation data is done bythe server calculation module 126 controlling the job tracking module204 a in the main server to assign a plurality of mapreduce tasks to thetask tracking module 204 b in each of the node servers (114-1 to 114-4),such that each of the node servers (114-1 to 114-4) is provided witheven amount of tasks.

In step S607, the calculation result processing module 128 may store thecalculation results. More specifically, the calculation resultprocessing module 128 may use a distributed data storage system command(Hive command) such as “LOAD DATA INPATH Output/sqrt′INTO TABLESquireRoot” to write the calculation results into the database locatedin the distributed data storage system 206. Particularly, thedistributed data storage system 206 may inquire for the calculationresults stored in the database by executing the query language based onSQL. For instance, the calculation result processing module 128 may usea command “SELECT * FROM SquireRoot SORT BY key” to read the calculationresults, so as to ensure that the calculation results are correctlywritten.

Thereafter, in step S609, the calculation result analysis module 132 mayanalyze the calculation results to verify the quality of each of thenode servers (114-1 to 114-4).

Based on above, in the method for verifying quality of server, thecalculation data is stored into the cloud computing platform file systemon the cloud computing platform first. Therefore, the calculation datamay be distributed over each server in the server cluster, so that eachserver is required to constantly exchange information to one anotherthrough the network. Accordingly, said method is capable of performingcomprehensive verification for calculations, network communications,memory accessing and writing/reading of storage devices in each serverin numerous server clusters, thereby ensuring quality of servers. Inaddition, numerous servers are serially connected through the cloudcomputing platform in the invention for conformably verifying quality ofnumerous servers in the server cluster, which may effectively improveperformance for verifying quality. Further, the operation condition ofeach server may be obtained through the registry generated after thecalculation job is executed, so as to improve operation quality of theservers.

What is claimed is:
 1. A method for verifying quality of server, usedfor verifying a plurality of servers constructed in a server cluster,and the method for verifying quality of server comprising: installing acloud computing platform in the servers in the server cluster, whereinthe cloud computing platform comprises a cloud computing platform filesystem and a mapreduce frame; creating an input file folder on the cloudcomputing platform file system and storing a calculation data into theinput file folder; creating a plurality of mapreduce tasks correspondingto a calculation job by the servers, accessing the calculation data inthe input file folder, and distributively executing the mapreduce tasksby using the mapreduce frame to obtain a plurality of calculationresults; storing the calculation results; and analyzing the calculationresults to verify a quality of each of the servers.
 2. The method forverifying quality of server as recited in claim 1, wherein the serverscomprise a main server and a plurality of node servers, wherein the stepof creating the mapreduce tasks corresponding to the calculation job bythe servers, accessing the calculation data in the input file folder,and distributively executing the mapreduce tasks by using the mapreduceframe to obtain the calculation results comprises: dividing thecalculation job into the mapreduce tasks by the main server; assigningthe mapreduce tasks to the node servers; and executing the mapreducetasks respectively by the node servers.
 3. The method for verifyingquality of server as recited in claim 2, further comprising: afterinstalling the cloud computing platform in the servers in the servercluster, writing a name of the main server and names of the node serversinto a corresponding profile; restarting the cloud computing platforminstalled in the servers; determining whether the node servers areconnected to the main server; and if the node servers are not connectedto the main server, restarting the cloud computing platform.
 4. Themethod for verifying quality of server as recited in claim 3, whereinthe cloud computing platform further comprises a distributed datastorage system, wherein the step of storing the calculation resultscomprises: transmitting the calculation results to the distributed datastorage system and storing the calculation results into a database. 5.The method for verifying quality of server as recited in claim 4,wherein the step of analyzing the calculation results to verify thequality of each of the servers comprises: determining an operationcondition of each of the servers during execution of the calculation jobaccording to a registry generated after the calculation job is executedby the server cluster.
 6. The method for verifying quality of server asrecited in claim 2, wherein the step of executing the mapreduce tasksrespectively by the node servers comprises: reading the calculation datafrom the input file folder by the node servers and executing a pluralityof mappers in the mapreduce tasks for the calculation data; andexecuting a plurality of reducers in the mapreduce tasks according tothe calculation results by the node servers.
 7. The method for verifyingquality of server as recited in claim 6, wherein the calculation job isa square root calculation.
 8. A system for verifying quality of server,used for verifying a plurality of servers constructed in a servercluster, and the system comprising: a calculation platform installingmodule, configured to install a cloud computing platform in the servers,wherein the cloud computing platform comprises a cloud computingplatform file system and a mapreduce frame; a file and data creatingmodule, configured to create an input file folder on the cloud computingplatform file system and store a calculation data into the input filefolder; a server calculation module, configured to control each of theservers to create a plurality of mapreduce tasks corresponding to acalculation job, access the calculation data in the input file folder,and distributively execute the mapreduce tasks by using the mapreduceframe to obtain a plurality of calculation results; a calculation resultprocessing module, configured to process and store the calculationresults; and a calculation result analysis module, configured to analyzethe calculation results to verify a quality of each of the servers. 9.The system for verifying quality of server as recited in claim 8,wherein the servers comprise a main server and a plurality of nodeservers, wherein the server calculation module is further configured tocontrol the main server to divide the calculation job into the mapreducetasks, wherein the server calculation module is further configured tocontrol the main server to assign the mapreduce tasks to the nodeservers, wherein the server calculation module is further configured tocontrol the node servers to execute the mapreduce tasks respectively.10. The system for verifying quality of server as recited in claim 9,wherein the system further comprises a server setting module, whereinthe server setting module is configured to, after installing the cloudcomputing platform in the servers in the server cluster, write names ofthe main server and the node servers into a corresponding profile,wherein the server setting module is further configured to restart thecloud computing platform installed in the servers, wherein the serversetting module is further configured to determine whether the nodeservers are connected to the main server, wherein if the node serversare not connected to the main server, the server setting module restartsthe cloud computing platform.
 11. The system for verifying quality ofserver as recited in claim 10, wherein the cloud computing platformfurther comprises a distributed data storage system, wherein thecalculation result processing module is further configured to transmitthe calculation results to the distributed data storage system and storethe calculation results into a database.
 12. The system for verifyingquality of server as recited in claim 11, wherein the calculation resultanalysis module is further configured to determine an operationcondition of each of the servers during execution of the calculation jobaccording to a registry generated after the calculation job is executedby the server cluster.
 13. The system for verifying quality of server asrecited in claim 9, wherein the server calculation module is furtherconfigured to control the node servers to read the calculation data fromthe input file folder and execute a plurality of mappers in themapreduce tasks for the calculation data, wherein the server calculationmodule is further configured to control the node servers to execute aplurality of reducers in the mapreduce tasks according to thecalculation results.
 14. The system for verifying quality of server asrecited in claim 13, wherein the calculation job is a square rootcalculation.